Unveiling the charge transfer dynamics steered by built-in electric fields in BiOBr photocatalysts

Construction of internal electric fields (IEFs) is crucial to realize efficient charge separation for charge-induced redox reactions, such as water splitting and CO2 reduction. However, a quantitative understanding of the charge transfer dynamics modulated by IEFs remains elusive. Here, electron microscopy study unveils that the non-equilibrium photo-excited electrons are collectively steered by two contiguous IEFs within binary (001)/(200) facet junctions of BiOBr platelets, and they exhibit characteristic Gaussian distribution profiles on reduction facets by using metal co-catalysts as probes. An analytical model justifies the Gaussian curve and allows us to measure the diffusion length and drift distance of electrons. The charge separation efficiency, as well as photocatalytic performances, are maximized when the platelet size is about twice the drift distance, either by tailoring particle dimensions or tuning IEF-dependent drift distances. The work offers great flexibility for precisely constructing high-performance particulate photocatalysts by understanding charge transfer dynamics.


Contents
is the continuity equation that describes a change in carrier density over time due to a difference between the incoming and outgoing flux of carriers as well as the recombination. After applying a uniform electric field, an electric term will show up in Equation (2) as the third term. The solution is derived in Equation (3), which indicates that 1) the non-equilibrium carrier will travel with a drift (group) velocity that is proportional to the external electric field and 2) the spatial distribution follows a characteristic Gaussian function as dictated by the exp [− The modulating effect of external electric field to non-equilibrium carrier dynamic is plotted in (b). (c) A sketch describes the spatial distribution evolution of electrons in a BiOBr platelet with a (001)/(200) facet junction. The electron distribution evolution over time is derived in the right panel. =2, =40 and =7 for a small case. The integrated profile exhibits a Gaussian curve. (c) =100, =40 and =7. It shows that, for a large case, a plateau feature is convoluted in the profile.
Supplementary Figure 11. Thickness measurement for BiOBr platelets by an electron energy loss spectroscopy (EELS) technique.
The specimen thickness could be calculated using the formula in the inset 8 . The mean free path could be estimated using numerical calculations in the literatures [9][10][11] .
In order to uncover how changes in the thickness of BiOBr photocatalysts affect its charge dynamic, we correlated the spatial distribution of Ag nanoparticles to the platelet thickness (using an electron energy loss spectroscopy (EELS) technique ( Supplementary Fig. 11)) 8-11 for a same BiOBr platelet. Overall, we have measured four BiOBr-2.5 platelets. Thereby, a relationship between its charge dynamics and its corresponding sample thickness could be established.
The principle of the measuring method is based on the reference ( Supplementary Fig. 11) [8][9][10][11] . The total integral intensity of the spectrum ( ) and the integral intensity of zero-loss peak (( 0 )) are connected with the thickness ( ) of BiOBr platelets, in the following formula: = ln ( The relationship between the thickness of BiOBr platelets and its drift distances/diffusion lengths is further plotted in Supplementary Fig. 13. Despite the changes in the thickness of BiOBr-2.5 platelets, the charge dynamics behavior of these BiOBr-2.5 platelets appears in a similar manner ( Supplementary Fig. 13), indicating that a change in thickness has little effect on the charge dynamic. To understand the effect of the optical absorption property of BiOBr platelets on photocatalytic performance, we have added the optical absorption property of BiOBr photocatalysts with different platelet sizes (2500, 500, 100, and 50 nm), which were shown in Supplementary Fig. 16. The results revealed that these BiOBr photocatalysts with different lateral sizes have a similar optical absorption property. Therefore, the photocatalytic activity difference should be caused by variation in charge transport, rather than the light absorption ability.  Supplementary Fig.  17a), indicating that the main structure of various BiOBr photocatalysts using different synthesis methods remains unchanged.

Supplementary
The surface area of various BiOBr photocatalysts is listed in Supplementary Fig. 17b. As expected, BiOBr-0.1 and BiOBr-0.1-B photocatalysts have a larger surface area than BiOBr-0.5 and BiOBr-0.5-B photocatalysts, but this difference is not very significant and is in the same order of magnitude. The optical absorption property, bandgap, and band edge positions of various BiOBr photocatalysts are recorded in Supplementary Fig. 17c-e. As shown in Supplementary Fig. 17c, all of the BiOBr photocatalysts exhibit comparable absorption edges and based on the plots of ( hν) 0.5 versus photon energy ( hν ) (Supplementary Fig. 17d), the bandgap energies of BiOBr photocatalysts are quite similar, which are calculated to be 2.73, 2.80, 2.71 and 2.76 eV for the BiOBr-0.1, BiOBr-0.1-B, BiOBr-0.5, and BiOBr-0.5-B photocatalysts, respectively. Additionally, the negative slope of the Mott-Schottky plots for BiOBr photocatalysts indicates the p-type characteristics ( Supplementary Fig. 17e), and their flat band potentials are measured to be 2.35, 2.27, 2.10, and 2.06 eV for the BiOBr-0.1, BiOBr-0.1-B, BiOBr-0.5, and BiOBr-0.5-B photocatalysts, respectively. Then, the energy band-gap diagram is presented in Supplementary  Fig. 17f, implying that all of the BiOBr photocatalysts have appropriate photoredox properties. To gain insight into the relationship between different synthesis methods and the behavior of charge dynamics/photocatalytic performance. We also test the charge dynamic and photocatalytic water oxidation performance for these BiOBr photocatalysts with different synthesis methods, and the results are shown in Supplementary Fig. 18. The drift distances of BiOBr-0.5-B and BiOBr-0.1-B are 50.5 and 51.1 nm, respectively. The diffusion lengths of BiOBr-0.5-B and BiOBr-0.1-B are 7.1 and 7.0 nm, respectively. When these results are compared with BiOBr-0.5 (drift distance: 48.7 nm, diffusion length: 7.3 nm) and BiOBr-0.1 (drift distance: 51.8 nm, diffusion length: 7.4 nm) photocatalysts, the differences observed are minor and could be considered negligible, revealing that different synthesis methods have little effect on the charge dynamics of BiOBr photocatalysts. Furthermore, the photocatalytic water oxidation performance of BiOBr photocatalyst is carried out in Supplementary Fig. 18i. The performances of BiOBr-0.1-B and BiOBr-0.5-B photocatalysts are 86 and 50 μmol·h -1 , respectively, which are comparable to the BiOBr-0.1 (93 μmol·h -1 ) and BiOBr-0.5 (53.9 μmol·h -1 ) photocatalysts, implying that the water oxidation capacities of BiOBr photocatalysts with similar lateral size are close. Therefore, all of these results show that the different synthesis methods have little effect on the chemical, physical, and optical absorption properties of BiOBr photocatalysts as well as the behavior of charge dynamic and their photocatalytic water oxidation performance. Figure 19. The effect of sample thickness on the charge transfer kinetics. TEM images of photo-deposited Ag nanoparticles on the different lateral sizes and thickness of BiOBr platelets with the corresponding statistical histogram of distance from the center of Ag nanoparticles to the edges of BiOBr platelets: (a-c) BiOBr-0.5, (d-j) BiOBr-0.1 platelets. Source data are provided as a Source Data file.

Supplementary
To investigate the effect of different lateral sizes on their charge dynamic behaviors, we photo-deposited Ag nanoparticles on the surface of various BiOBr platelets. The thickness, drift distance, and diffusion length of these BiOBr platelets were shown in Supplementary Fig. 19 and Table 1. Lining up of Ag nanoparticles near the platelet edges works for BiOBr-0.5 and BiOBr-0.1 photocatalysts. The drift distance/diffusion length of BiOBr-0.5 and BiOBr-0.1 photocatalysts are 48.7/7.3 ( Supplementary Fig. 19a-c) and 51.8/7.4 nm ( Supplementary Fig. 19d-j), respectively. Figure 20. Photo-deposition of Ag nanoparticles on the surfaces of BiOBr platelets when their thickness are reduced to ~50 nm. (a) TEM image of photo-deposited Ag nanoparticles on the BiOBr-0.05 platelets with the corresponding statistical histogram of its (b) thickness. Note that Ag nanoparticles with dark contrasts randomly distribute on the surface of BiOBr-0.05 platelets and the carbon film of the Cu grid, this might be due to a reduction of platelet thickness (mean thickness: 17 nm), which decreases the width of the space charge region in the thickness direction, weakening the strength of 12 . The internal electric field within the facet junction became weaker to drive the directional migration of charge carriers, leading to a random distribution of Ag nanoparticles as probes of photo-generated electrons. Source data are provided as a Source Data file. To estimate the charge mobility in BiOBr systems, we tested the time-resolved lifetime measurements of BiOBr platelets ( Supplementary Fig. 21). The overall lifetime of electrons for BiOBr-0.05, 0.1, 0.5 and 2.5 photocatalysts are 1.03, 3.21, 1.76, and 1.03 ns, respectively.

Supplementary
Taking the BiOBr-2.5 photocatalyst as an example, the value of its overall electron lifetime is 1.35 ns. Thus, the actual flight time of electrons ( 1 ) with the facet junction should be less than 1.35 ns. Here we assume that 1 is close to 1.35 ns.
For the value of electric field ( ), we assume that it is a uniform electric field. The strength of an electric field is ΔV/d, where ΔV is the potential difference and d is the distance. ΔV is related to the surface voltage 13 , which is 0.1mV from the previous literatures 14,15 . For the value of d, we assume that d is equivalent to the drift distance of electrons (~55.7 nm).
Finally, using the equation of = /( 1 )=( × )/(ΔV × 1 ), and the is derived as 2.30 × 10 2 2 /( • ). The theoretical charge mobility is 5.33 × 10 2 2 /( • ) 16 , which is basically in the same magnitude compared to our results, revealing that our estimation is reliable. To examine the charge dynamic behavior in BiVO4 photocatalysts, we also photo-deposited Ag nanoparticles on their surfaces. As shown in Supplementary Fig. 24, Ag nanoparticles accumulate around the edges of the top facets of {010} for BiVO4 photocatalysts (Supplementary Fig. 24a-g). After statistical analysis of the distribution for Ag nanoparticles in the Ag/BiVO4 system, the diffusion length of electrons within Ag/BiVO4 photocatalysts is 64 nm ( Supplementary  Fig. 24h), which is close to the value of ~70 nm reported in the literature 17 . Figure 25. Photo-deposition of Ag nanoparticles on the surfaces of some common photocatalysts. TEM images and EDS maps of photo-deposited Ag nanoparticles on (a) WO3, (b) ZnO, (c) CeO2, (d) CdS, and (e) Ta3N5 photocatalysts. Note that Ag nanoparticles randomly distributed on the surface of these photocatalysts.

Supplementary
Ag nanoparticles were also photo-deposited on the surface of WO3, ZnO, CeO2, CdS, and Ta3N5 photocatalysts. As shown in Supplementary Fig. 25, Ag nanoparticles randomly dispersed on the surface of WO3, ZnO, CeO2, CdS, and Ta3N5 photocatalysts without forming a regular clustering pattern. To understand the observed photo-deposition differences, we have investigated the literature and found that the BiVO4 photocatalysts have two spatially separated reductive {010} and oxidative {110} surfaces 18 . The formation of {010}/{110} facet junctions (defined as a homojunction between neighboring facets in a single-crystalline semiconductor) 3-5 is beneficial for expediating charge separation. Facet junctions were not observed for the above photocatalysts. Hence, we propose this approach might be applicable to photocatalysts with spatially separated reductive and oxidative surfaces.